Apparatus and method for forming and analyzing connected roads

ABSTRACT

Aspects of the disclosure provide an apparatus and a method for forming and analyzing connected roads. The apparatus can include processing circuitry. The processing circuitry determines, based on a first map of a region having road segments, a second map having connected roads. One of the connected roads is formed by combining a plurality of the road segments and is longer than a threshold. The processing circuitry determines road complexity of one of the connected roads in the second map for route planning and/or testing.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

U.S. Pat. No. 9,305,380 B2 describes a method for conflating geometriesto a road in a map region for an electronic mapping service. The methodreceives a first geometry representing a road. The method receivesseveral geometries arranged such that a gap representing the road isbetween the geometries. The gap is not aligned with the first geometryrepresenting the road. The method expands the geometries toward thefirst geometry such that the geometries converge at the first geometry.The road geometry is for drawing over the plurality of other geometriesby a client mapping application.

SUMMARY

According to the present disclosure, there is provided an apparatus anda method for forming and analyzing connected roads. The apparatus caninclude processing circuitry. The processing circuitry determines, basedon a first map of a region having road segments, a second map havingconnected roads. One of the connected roads is formed by combining aplurality of the road segments and is longer than a threshold. Theprocessing circuitry determines road complexity of one of the connectedroads in the second map for route planning and/or testing. In anexample, the road segments are shorter than the threshold. The roadcomplexity includes, but is not limited to, information of at least oneof: ramps, curves, lanes, orientation, hills, tunnels, and speed limitof the one of the connected roads. The apparatus can further includeinterface circuitry that is configured to obtain the first map.

The processing circuitry may further be configured to determine whetherthe first map is to be divided. When the first map is determined to bedivided, the processing circuitry can divide the first map into multiplefirst sub-maps. The processing circuitry can determine, based on thefirst sub-maps, second sub-maps by connecting the road segments intoconnected sub-roads and combine the sub-roads in the second sub-mapsinto the connected roads in the second map. In an example, theprocessing circuitry is configured to determine whether the first map isto be divided based on at least one of: a number of the road segmentsand a size of the region.

One of the connected roads may include a ramp. The processing circuitryis further configured to determine merge achievability for the rampbased on information of the ramp, the one of the connected roads, and avehicle to merge onto the one of the connected roads. In an example, theprocessing circuitry is further configured to implement a merge modelthat includes a transition period when the vehicle is controlled by adriver of the vehicle and an automatic period when the vehicle iscontrolled automatically. The information can include a ramp distance, aspeed limit of the one of the connected roads, a maximum speed of thevehicle, and a maximum acceleration of the vehicle.

In an example, the processing circuitry is further configured to obtainat least one route based on the road complexity.

According to the present disclosure, there is provided a non-transitorycomputer readable storage medium having instructions stored thereon thatwhen executed by processing circuitry causes the processing circuitry toperform a method. The method can include determining, based on a firstmap of a region having road segments, a second map having connectedroads where one of the connected roads is formed by combining aplurality of the road segments and is longer than a threshold. Themethod further includes determining road complexity of one of theconnected roads in the second map for route planning and/or testing.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of this disclosure that are proposed as exampleswill be described in detail with reference to the following figures,wherein like numerals reference like elements, and wherein:

FIG. 1 is a schematic of an exemplary apparatus 100 according to thepresent disclosure;

FIG. 2 is a flowchart outlining an exemplary process 200 according tothe present disclosure;

FIG. 3 is a flowchart outlining an exemplary process 300 according tothe present disclosure;

FIG. 4A shows a first map 401 for a region 400;

FIG. 4B shows first sub-maps 401A-D;

FIG. 4C shows second sub-maps 402A-D;

FIG. 4D shows a second map 402 including connected roads determinedbased on the first map according to the present disclosure;

FIG. 5A-C show examples of road complexity analysis according to thepresent disclosure;

FIG. 5D shows results of a road complexity analysis according to thepresent disclosure;

FIGS. 6A-6E show examples of road complexity analysis results accordingto the present disclosure;

FIGS. 7A-7C show examples of merging, diverging, and merging/diverging;

FIG. 8A shows a first merge model according to the present disclosure;

FIG. 8B shows a first speed versus position relationship according tothe present disclosure;

FIG. 8C shows a second merge model according to the present disclosure;

FIG. 8D shows a second speed versus position relationship according tothe present disclosure;

FIGS. 9A-9D show exemplary displays of merging achievability overlaid onthe second map 402 according to the present disclosure;

FIG. 9E shows a histogram 910 of the merging achievability;

FIGS. 10A-10L shows histograms for level I-V merge achievability;

FIG. 11 shows a histogram 1100 of merge distances of a large number oframps in a region;

FIG. 12 shows a histogram 1200 of merge/diverge distances of a largenumber of ramps in a region;

FIGS. 13A-13L shows histograms for level I-V merge/divergeachievability.

DETAILED DESCRIPTION

A first map, such as a high-definition (HD) map, of a region can haveshort road segments, such as road segments 5 to 100 meters long. Certainroad complexity in the region, such as information of curves, hills,ramps, orientations, and the like, is determined over longer distances,such as longer than 100 meters. According to aspects of the disclosure,a plurality of short road segments in the first map can be combined orconnected into a connected road in a second map, and thus the second mapincluding connected roads can be determined based on the first map.Subsequently, the road complexity of the region can be determined basedon the connected roads in the second map. Further, route planning can beperformed based on the road complexity.

FIG. 1 is a schematic of an exemplary apparatus 100 according to thepresent disclosure including processing circuitry 130, input interfacecircuitry 151, output interface circuitry 152, communication devices170, and memory 140.

The input interface circuitry 151 can be configured to receive mapinformation of a region, such as a HD map having short road segments andthe like. FIG. 4A shows a first map 401 received by the input interfacecircuitry 151 for a region 400. The first map 401 has road segments411-437. The first map 401 can include first nodes N1(1)-(6), secondnodes N2(1)-(18), and third nodes N3(1)-(4). Each of the first nodesN1(1)-(6) is located at an edge of the first map 401 and is an end ofonly one road segment in the first map 401. Each of the second nodesN2(1)-(18) can separate two adjacent road segments and is an end of thetwo adjacent road segments. For example, the second node N2(1) separatesthe road segments 411-412 and is an end of the two adjacent roadsegments 411-412. Each of the third nodes can separate more than twoadjacent road segments. For example, the third node N3(1) separates theroad segments 415, 418, and 419.

The road segments 411-437 can be categorized into first segments (alsoreferred to as dead ends) and second segments (also referred to asconnected road segments). The first segments include the road segments411, 416, 426, 428, 429, and 437 and the second segments includeremaining road segments, such as the road segments 412-415, in the firstmap 401. Each first segment includes one of the first nodes N1(1)-(6)and one of the second nodes N2(1)-(18) or the third nodes N3(1)-(4).Each first segment is located at an edge of the first map 401 or theregion 400. Each second segment includes two of the second nodesN2(1)-(18) and/or the third nodes N3(1)-(4).

The first map 401 includes ramps (also referred to as connected links)471-481 that are associated with the road segments 413, 415, 417, 420,423, 427, 426, 434, 431, 436, and 429, respectively. A ramp can refer toa road that is used for a vehicle to merge onto and/or diverge fromanother road (e.g., a highway). In an example, the first map 401 caninclude other roads or road segments (not shown) that are connected tothe ramps 471-481.

By way of example, a subset of the road segments 411-437 is shorter thana first threshold, such as 100 meters, and the first map 401 is a HD mapwhere the road segments 411-437 are shorter than the first threshold.

The map information can also include one or more road characteristicsfor one or more of the road segments 411-437. The road characteristicscan include information of lanes, ramps, elevations (or altitudes),tunnels, speed limits, orientations (e.g., an angle of a road segmentwith respect to a west-east direction), and the like.

The input interface circuitry 151 can also be configured to receive datarelated to route planning, such as a starting point, a destination,criteria used to select an optimal route from a plurality of routes, andthe like. For example, the input interface circuitry 151 can receivetraffic information or data related to route planning/testing from anysuitable external sources. The traffic information can be real-timetraffic information or previously collected traffic information. In anexample, the traffic information can be used to determine roadcomplexity, such as merge achievability. The input interface circuitry151 can include any suitable individual device or any suitableintegration of multiple devices such as touch screens, keyboards,keypads, a mouse, joysticks, microphones, universal series bus (USB)interfaces, optical disk drives, wireless receivers, and the like. Theinput interface circuitry 151 can also include a controller that convertdata into electrical signals and send the electrical signals to theprocessing circuitry 130.

Referring to FIG. 1 , the processing circuitry 130 can include a roadsegment connection module (also referred to as a connection module) 131,a road complexity analysis module (also referred to as an analysismodule) 132, and a routing module 133. The connection module 131 can beconfigured to receive and process the map information from, for example,the input interface circuitry 151. In an example, the connection module131 receives the first map 401 shown in FIG. 4A and combines the roadsegments 411-437 into connected roads 461-469, as shown in FIG. 4D, forexample, based on geometric relationship of the road segments. Referringto FIG. 4A, at one of the second nodes N2(1)-(18), such as N2(1), theconnection module 131 can connect two adjacent road segments, such asthe road segments 411-412 to form a portion of the connected road 461.At one of the third nodes N3(1)-(4), such as N3(1), the connectionmodule 131 can determine that N3(1) is an end of the connected road 461.Accordingly, referring to FIGS. 4A and 4D, the connection module 131 canbe configured to combine the road segments 411-415 into the connectedroad 461. Similarly, the connection module 131 can combine the roadsegments 416-418 into the connected road 462, combine the road segments419-421 into the connected road 463, combine the road segments 432-434into the connected road 464, combine the road segments 435-437 into theconnected road 465, combine the road segments 429-431 into the connectedroad 466, combine the road segments 422-424 into the connected road 467,combine the road segments 425-426 into the connected road 468, andcombine the road segments 427-428 into the connected road 469.

The region 400 can have any suitable size and shape, such as arectangle, a square, a circle, or the like. Instead of combining aplurality of road segments directly into a connected road as describedabove, referring to FIG. 4B, the connection module 131 can also dividethe region 400 into a plurality of sub-regions 400A-D, and thus dividethe first map 401 into a plurality of first sub-maps 401A-D,respectively, for example, when a size of the region 400 exceeds a sizethreshold, when a number of the road segments 411-437 in the first map401 exceeds a number threshold, and/or the like. The first sub-maps401A-D are in the respective sub-regions 400A-D.

The connection module 131 can determine second sub-maps 402A-D based onthe respective first sub-maps 401A-D by combining road segments in eachof the first sub-maps 401A-D into connected sub-roads in the respectivesecond sub-map. More specifically, referring to FIGS. 4A-4C, theconnection module 131 can combine the road segments 411-413 into aconnected sub-road 441 and the road segments 436-437 into a connectedsub-road 442 to form the second sub-map 402A. The connection module 131can combine the road segments 416-418 into a connected sub-road 443 andthe road segments 414-415 into a connected sub-road 444 to form aportion of the second sub-map 402B. The second sub-map 402B alsoincludes the road segment 419 not combined with other road segments inthe sub-map 402B. The connection module 131 can combine the roadsegments 429-431 into a connected sub-road 445 to form a portion of thesecond sub-map 402C. The second sub-map 402C also includes the roadsegments 435 and 432 that are not combined with other road segments inthe sub-map 402C. Further, the connection module 131 can combine theroad segments 420-421 into a connected sub-road 446, the road segments433-434 into a connected sub-road 447, the road segments 422-424 into aconnected sub-road 448, the road segments 425-426 into a connectedsub-road 449, and the road segments 427-428 into a connected sub-road450 to form the second sub-map 402D. As described above, the secondsub-maps 402A-D can include connected sub-roads. The second sub-maps402A-D can also include one or more road segments, such as the roadsegments 419, 432, and 435, that are not connected with other roadsegments in the respective second sub-maps.

Referring to FIGS. 4C-4D, the connection module 131 can determine theconnected roads 461-469 in the second map 402 based on the sub-roads441-450 and the road segments 419, 432, and 435 in the respective secondsub-maps 402A-D. For example, the connection module 131 combines thesub-roads 441 and 444 into the connected road 461; combines the sub-road446 and the road segment 419 into the connected road 463; combines thesub-road 447 and the road segment 432 into the connected road 464;combines the sub-road 442 and the road segment 435 into the connectedroad 465. The connected road 462 is the sub-road 443, the connected road466 is the sub-road 445, the connected road 467 is the sub-road 448, theconnected road 468 is the sub-road 449, and the connected road 469 isthe sub-road 450. Accordingly, the second map 402 includes the connectedroads 461-469.

The methods described above can be suitably adapted to scenarios where aroad segment is located in more than one first sub-maps.

The analysis module 132 can determine road complexity of a map in aregion, for example, for route planning, route testing, and/or the like.The road complexity can be used in field operation test planning,vehicle evaluation, automated driving software development, and thelike. The road complexity can include information of curves, hills,ramps, road orientation, lanes, speed limits, and the like. The roadcomplexity can be determined based on roads, such as connected roads,having lengths longer than the first threshold.

FIGS. 5A-5C show examples of road complexity analysis according to thedisclosure. In FIG. 5A, curve information, e.g., a number of curves perunit length, of a road 501 can be determined. In an example, the road501 is obtained by combining a plurality of shorter road segments531-539 using the connection module 131. The curve information may notbe determined accurately based on individual road segments 531-539,however, can be determined accurately based on the connected road 501.Referring to FIG. 5A, the road 501 is 10 kilometers (km) long and thereare curves 1-4 in the road 501, and thus the curve information is 0.4curves per km.

In FIG. 5B, lane information of the road 501 can be determined. Forexample, the lane information can be represented by an average number oflanes. Referring to FIG. 5B, the road 501 includes two portions 501A-Bseparated by a divider 510. The portion 501A has 4 lanes and the portion501B has 3 lanes. Any suitable method can be used to calculate theaverage number of lanes for the road 501. In FIG. 5B, the average numberof lanes is calculated based on the numbers of lanes and respectivelengths of the portions 501A-B, and thus the average number of lanes is3.2 lanes.

In FIG. 5C, road orientation of the road 501 can be determined. The roadorientation can describe how much a road or portions of the road is/areoriented along a certain direction, such as a west to east direction, asouth to north direction, or the like. For example, the road orientationof a “60% low Sun-angle” indicates that 60% of the road 501 is alignedto the west to east direction. To obtain the road orientation, theanalysis module 132 can divide the road 501 into portions 521-525 bydividers 541-544, respectively. One of the portions 521-525 can bedetermined to be associated with a low-Sun angle when an angle betweenthe portion and the west to east direction is less than an angularthreshold. For example, the portion is determined to be associated withthe low-Sun angle when the portion is substantially parallel to the westto east direction. Otherwise, when the angle between the portion and thewest to east direction is equal to or larger than the angular threshold,the portion is determined not to be associated with the low-Sun angle.Referring to FIG. 5C, the portions 521, 523, and 525 are determined tobe associated with the low-Sun angle and the portions 522 and 524 aredetermined not to be associated with the low-Sun angle. Accordingly, theroad orientation of the road 501 is “60% low Sun-angle”. Of course,other suitable criteria and/or methods can be used to describe orcalculate the road orientation.

FIG. 5D shows results of a road complexity analysis according to thedisclosure. A map 500 includes roads 501-503. In an example, the roads501-503 are connected roads obtained from a plurality of shorter roadsegments, respectively. The analysis module 132 can analyze the roads501-503, respectively, using, for example, the methods described aboveand obtain the road complexity analysis results described in Table 1.

TABLE 1 Road complexity analysis results Curve Lane informationinformation Orientation (curves (number of [% of low- Road per km)Lanes) Sun angle] 501 0.4 3.2 60 502 0.2 4 0 503 0.2 4 80

As seen from Table 1, the road 501 has more curves per km than the roads502-503. The roads 502-503 differ in the respective orientations: theroad 502 mainly runs from the south to the north while the road 503mainly runs from the west to the east.

The routing module 133 can be configured to implement route planningbased on the road complexity, for example, obtained by the analysismodule 132 and certain criteria. The criteria can be associated with,curve information, lane information, orientation, ramp information, andthe like. In various examples, the criteria is a ‘hardest route’, an‘easiest route’, a curviest route’, a route having low-Sun angle, aroute having most ramps, or the like. The routing module 133 can obtaina plurality of routes based on a starting point and a destination byusing suitable method or algorithms, such as “k shortest path routing”algorithms based on Dijkstra's algorithm, Bellman Ford algorithm, andthe like. Further, the routing module 133 can select at least one of theplurality of routes based on the criteria. For example, the at least oneof the plurality of routes can be the ‘hardest route’ that includes, forexample, one or more of at least a first number of curves per km, atleast a second number of lanes, at least a third percentage of low-Sunangle, and at least a fourth number of ramps that are difficult tomerge. The at least one of the plurality of routes can also be the‘easiest route’ for implementing a comfort test, the curviest route fora lane center test, the low-Sun angle road for a camera test, the mostramps road for a dynamic handling test, or the like.

The output interface circuitry 152 can be configured to output data,such as a map having connected roads, road complexity analysis results,one or more routes that are planned based on the road complexityanalysis result, and the like. The output interface circuitry 152 caninclude any suitable individual device or any suitable integration ofmultiple devices such as display devices, audio devices, such asspeakers, wireless transmitters, and the like. The output interfacecircuitry 152 can also include a controller that convert electricalsignals from the processing circuitry 130 to the data, such as visualsignals including text messages used by a display device, audio signalsused by a speaker, and the like. In an example, a component of the inputinterface circuitry 151 and a component of the output interfacecircuitry 152 can be combined into a device. For example, the outputinterface circuitry 152 can be configured to output an image on aninteractive screen and the input interface circuitry 151 can beconfigured to receive data generated by a stylus interacting with theinteractive screen.

The communication devices 170 can be configured to communicate with anysuitable device using any suitable communication technologies, such aswired, wireless, fiber optic communication technologies, and anysuitable combination thereof. The communication devices 170 can includeany suitable communication devices using any suitable communicationtechnologies. In an example, the communication devices 170 can usewireless technologies, such as IEEE 802.15.1 or Bluetooth, IEEE 802.11or Wi-Fi, mobile network technologies including such as global systemfor mobile communication (GSM), universal mobile telecommunicationssystem (UMTS), long-term evolution (LTE), fifth generation mobilenetwork technology (5G) including ultra-reliable and low latencycommunication (URLLC), and the like. The communication devices 170 canreceive traffic information related to route planning from suitableexternal sources. The traffic information can be real-time trafficinformation or previously collected traffic information. In an example,the traffic information can be used to determine road complexity, suchas merge achievability.

The input interface circuitry 151 and/or the output interface circuitry152 can include the communication devices 170. The communication devices170 can also be configured to receive the map information and/or outputdata, such as a map having connected roads, road complexity analysisresults, one or more routes that are planned based on the roadcomplexity analysis result, and the like.

The memory 140 is configured to store maps, such as a map having shortroad segments, a HD map, a map having connected roads, and the like. Thememory 140 can also store road complexity analysis results, criteria forroute planning, routes, and programs. The programs can include methodsimplemented by the processing circuitry 130 as described above.Information in the memory 140 can be modified or updated by theprocessing circuitry 130, such as the connection module 131, theanalysis module 132, and the routing module 133. The memory 140 can be anon-volatile storage medium. The memory 140 can include bothnon-volatile and volatile storage media. A portion of the memory 140 canbe integrated into the processing circuitry 130. The memory 140 can belocated remotely and communicate with the processing circuitry 130 via awireless communication standard using the communication devices 170.

In the FIG. 1 example, the components are coupled together by a busarchitecture including a bus 150. Other suitable interconnectiontechniques can also be used.

One or more components of the input interface circuitry 151, the outputinterface circuitry 152, the communication devices 170, the processingcircuitry 130, and the memory 140 can be made by discrete devices orintegrated devices. The circuits for one or more of the input interfacecircuitry 151, the output interface circuitry 152, the communicationdevices 170, the processing circuitry 130, and the memory 140 can bemade by discrete circuits, one or more integrated circuits,application-specific integrated circuits (ASICs), and the like. Theprocessing circuitry 130 can also include one or more central processingunits (CPUs), one or more graphic processing units (GPUs), dedicatedhardware or processors to implement neural networks, and the like.

FIG. 2 is a flowchart outlining an exemplary process 200 implementedusing the apparatus 100 shown in FIG. 1 . The process 200 can be used tocombine short road segments in a first map into connected roads in asecond map, determine road complexity of a region based on the connectedroads in the second map, and perform route planning based on the roadcomplexity. The first map 401 shown in FIG. 4A is used to illustrate theprocess 200. The process 200 starts at S201 and proceeds to S210.

At S210, the second map is determined based on the first map bycombining the road segments in the first map into the connected roads inthe second map. As described above, the road segments 411-437 in FIG. 4Acan be directly combined into the connected roads 461-469 in FIG. 4D.For example, the road segments 411-415 can be combined into theconnected road 461.

Alternatively, the first map 401 can be divided into the first sub-maps401A-D (FIG. 4B) and the road segments in each of the first sub-maps401A-D are combined into the connected sub-roads in the second sub-maps402A-D (FIG. 4C). Subsequently, the sub-roads in the second sub-maps402A-D are connected to form the connected roads 461-469 (FIG. 4D). Forexample, the road segments 411-413 in the first sub-map 401A arecombined to form the sub-road 441 and the road segments 414-415 in thefirst sub-map 401B are combined to form the sub-road 444. Further, thesub-roads 441 and 444 are combined into the connected road 461. Thesecond sub-maps 402A-D can be determined in a parallel process from therespective first sub-maps 401A-D, thus can be determined faster thandetermining the second map 402 directly from the first map 401.

At S220, road complexity can be determined based on the connected roadsin the second map, for example, for route planning. The road complexitycan be used in field operation test planning, vehicle evaluation,automated driving software development, and the like. As describedabove, the analysis module 132 can implement the step S220. The roadcomplexity can include information related to curves, lanes,orientation, ramps, hills, tunnels, speed limits, and the like. Anysuitable methods can be used to represent the road complexity of theconnected roads in the second map. Table 2 shows an exemplary summary ofthe road complexity of the connected roads 461-469.

TABLE 2 Road complexity analysis results Speed Number Number Numberlimit Length Road of ramps of lanes of curves Hills Tunnels (mph) (km)461 2 3.2 2 0 0 65 10 462 1 4 3 0 0 77 7 463 1 3 1 0 1 54 7.5 464 1 3.51 1 0 76 6 465 1 5 1 0 0 50 9 466 2 3.5 1 0 0 77 10 467 1 5 0 0 1 65 5468 1 4 1 0 0 60 5 469 1 4 0 0 0 65 2

Table 3 shows an example of classification analysis. Road informationcan be derived based on the road complexity analysis. A road can beclassified into a road having ‘many ramps’ when a number of ramps per kmin the road is larger than, for example, 2. A road can be classifiedinto a road having ‘many lanes’ when an average number of lanes in theroad is larger than, for example, 4. A road can be classified into aroad having ‘many curves’ when a number of curves per km in the road islarger than, for example, 5. A road can be classified into a road having‘many hills/valleys’ when an altitude inflection in the road is largerthan, for example, 0.015 per km. A road can be classified into a roadhaving ‘tunnels’ when a number of tunnels in the road is larger than,for example, 0. A road can be classified into a road having ‘low speed’when an average speed limit of the road is less than, for example, 55mph. A road can be classified into a road having ‘high speed’ when anaverage speed limit of the road is larger than, for example, 75 mph. Inan example, other road information, such as whether a merge is easy ordifficult, can also be determined. Accordingly, based on the aboveclassification and Table 2, none of the connected roads 461-469 has‘many ramps’ or has many curves; the connected road 465 has ‘manylanes’; the connected road 464 has ‘many hills/valleys’; the connectedroads 463 and 467 have ‘tunnels’; the connected roads 463 and 465 have‘low speed’; and the connected roads 462, 464, and 466 have ‘highspeed’. The total length of the connected roads 461-469 is 61.5 km. Ofcourse, a road can be classified to have ‘many ramps’, ‘many lanes’, orthe like using other criteria.

TABLE 3 Road complexity analysis results Length Classification Meaning(km) Many ramps A number of ramps 0 per km > 2 Many lanes An averagenumber 9 of lanes > 4 Many curves A number of curves 0 per km > 5 Manyhills/ An altitude inflection 6 valleys per km > 0.015 Tunnel A numberof tunnels > 0 12.5 Low speed An average speed < 16.5 55 MPH High speedAn average speed > 23 75 MPH Total length 61.5

Additionally or alternatively, the road complexity analysis results canbe displayed graphically. FIGS. 6A-6E show examples of highlighting theroad complexity analysis results. The second map 402 including theconnected roads 461-469 is shown in each of the FIGS. 6A-6E. Referringto FIG. 6A, roads having ‘many lanes’ are highlighted, and thus theconnected road 465 (dashed line) is overlaid on the second map 402.Referring to FIG. 6B, roads having ‘many hills/valleys’ are highlighted,and thus the connected road 464 (dashed line) is overlaid on the secondmap 402. Referring to FIG. 6C, roads having ‘tunnels’ are highlighted,and thus the connected roads 463 and 467 (dashed line) are overlaid onthe second map 402. Referring to FIG. 6D, roads having ‘low speeds’ arehighlighted, and thus the connected roads 463 and 465 (dashed line) areoverlaid on the second map 402. Referring to FIG. 6E, roads having ‘highspeeds’ are highlighted, and thus the connected roads 462, 464, and 466(dashed line) are overlaid on the second map 402. Various displaymethods can be used to visualize the road complexity analysis results.Different colors can be used to highlight different road information,and thus, for example, roads having ‘many lanes’ and roads having ‘manyhills/valleys’ can be overlaid on the second map 402 in a same figure.

In addition to the information related to curves, lanes, orientation,hills, tunnels, speed limits, and the like, merging informationassociated with a ramp can also be determined. A ramp can refer to aroad that is used for a vehicle to merge onto another road (e.g., ahighway), to diverge from another road, to merge onto and then divergefrom another road, and the like. A ramp can also include a plurality ofshort ramp segments. Therefore, the plurality of ramp segments can beconnected into the ramp by, for example, the connection module 131 usingsimilar or identical methods as described above. In various examples,ramp information and vehicle information are used to determine mergingachievability, e.g., how easy or difficult a vehicle can merge onto aroad via the ramp, and merging/diverging achievability, e.g., how easyor difficult a vehicle can merge/diverge onto/from a road via the ramp.

FIGS. 7A-7C show examples of merging, diverging, and merging/divergingaccording to the disclosure. FIG. 7A shows a merging example 700A. Aroad 710A has lanes 712A-713A. In an example, the road 710A is ahighway. Vehicles 722A-723A run on the lanes 712A-713A, respectively. Aramp 711A is located next to the lane 712A and has a ramp distance D1. Avehicle 721A on the ramp 711A is to merge onto the road 710A. Mergingachievability, i.e., how easy or difficult for the vehicle 721A to mergeonto the road 710A via the ramp 711A, can be determined based on vehicleinformation of the vehicle 721A, the ramp information of the ramp 711A,and the road information of the road 710A. The vehicle information caninclude acceleration information (e.g., a maximum acceleration, aminimum acceleration), speed information (e.g., a maximum speed), andthe like. The ramp information can include the ramp distance D1, curveinformation, speed information, hill/valley information, and the like.The road information can include speed information and the like. Themerging achievability can also depend on a method (also referred to as amerge logic or a merge model) used to determine the merge achievability.In an example, the merge achievability depends on a merging speed, e.g.,a speed of the vehicle when the vehicle merges onto the road 710A.

FIG. 8A shows a first merge model used to determine merge achievability.The first model includes three merging steps (also referred to as steps)A1-C1. In the step A1, the vehicle 721A attempts automatic merging fromthe ramp 711A to the lane 712A. The vehicle 721A can search a targetspace to merge, adjust a speed of the vehicle 721A, and steer thevehicle 721A into the lane 712A when there is enough space in the lane712A for the vehicle 721A. Of course, the speed of the vehicle 721A iswithin a maximum speed of the vehicle 721A. In an example, the speedincreases during the step A1 as shown in a corresponding first speedversus position relationship in FIG. 8B. When a distance between thevehicle 721A and an end of the ramp 711A reaches a first distance, suchas 100 m, the vehicle 721A can transition into the step B1. In the stepB1, the vehicle 721A starts a speed management while attempting theautomatic merging. The vehicle 721A can also search a target space tomerge and steer the vehicle into the lane 712A when there is enoughspace in the lane 712A for the vehicle 721A. In an example, the speedcontinues to decrease. In an example, the speed decreases in a firstportion of the step B1 and then increases in a second portion when thereis enough space in the lane 712A (indicated by an arrow 731). When thedistance between the vehicle 721A and the end of the ramp 711A reaches asecond distance, such as 40 m, the vehicle 721A can transition into thestep C1. In the step C1, the vehicle 721A stops automatically beforereaching an end of the ramp 711A without steering to the lane 712A. Inan example, the vehicle 721A decelerates at an acceleration of 0.35 G.The stopping process in the step C1 can be too sudden and does not givea driver of the vehicle 721A enough time to recover. In order to have asmoother transition and give the driver an opportunity to recover, asecond merge model in FIGS. 8C-D can be used.

FIG. 8C shows an example of the second merge model. FIG. 8D shows asecond speed versus position relationship where a speed of the vehicle721A versus a position of the vehicle 721A during the merge process inFIG. 8C is shown. The second merge model can include 4 steps: A2-D2. Thestep A2 is similar to the step A1, and thus detailed descriptions areomitted for purposes of brevity. In an example, when a distance betweenthe vehicle 721A and the end of the ramp 711A reaches a third distance,the vehicle 721A can transition into the step B2. The third distance canbe different from the first distance. In an example, when a distancebetween the vehicle 721A and the end of the ramp 711A reaches a fourthdistance, the vehicle 721A can transition from B2 into the step D2. Thefourth distance can be different from the second distance. At the end ofstep B2, a transition demand (TD) is requested where a control of thevehicle 721A is handed over to the driver. In an example, the speeddecreases in a first portion of the step B2 and then increases in asecond portion when there is enough space in the lane 712A (indicated byan arrow 732). In the step D2, the vehicle 721A is controlled by thedriver. A duration of the step D2, i.e., a TD duration, can be set inthe TD request, pre-determined, or the like. In an example, adeceleration of the vehicle 721A in the step D2 is less than that in thestep C1 in FIG. 8A. At the end of the step D2, the vehicle 721A canenter the step C2, which can be identical or similar to the step C1 inFIG. 8A, and thus detailed descriptions are omitted for purposes ofbrevity. The vehicle 721A can stop before reaching the end of the ramp711A in the step C2. In an example, the additional step D2 has adeceleration less than that of the step C1 and results in a relativelysmooth transition.

Referring to FIGS. 8B and 8D, the first speed versus positionrelationship in FIG. 8B can be different from the second speed versusposition relationship in FIG. 8D. For example, the speed can decreasemore rapidly in a portion 760 of the step B1 in the first speed versusposition relationship than that in the step D2 of the second speedversus position relationship.

The first and the second merge models can be used to determine the mergeachievability. The merge achievability can be categorized into, forexample, multiple levels I-V. The vehicle 721A can merge onto the lane712A via the ramp 711A in the levels I, II, III, IV, and V when an intervehicle time T on the road 710A or the lane 712A is less than 1 s,between 1 and 1.5 s, between 1.5 and 2 s, between 2 and 2.5 s, andlarger than 2.5 s, respectively. The inter vehicle time can refer to anaverage time lapse of two adjacent vehicles on the lane 712A passingthrough a same target on the lane 712A. The levels I-V can also bereferred to as ‘ultra achievability’, ‘high achievability’, ‘mediumachievability’, ‘low achievability’, and ‘not achievable’, respectively.Therefore, the ultra achievability means that the vehicle 721A can mergeonto the lane 712A when the inter vehicle time for the lane 712A is lessthan 1 s. An inter vehicle distance D can be determined by using D=T×Vwhere T is the inter vehicle time and V can be determined based on aspeed limit of the road 710A. V can be the speed limit or a fraction,such as 80% of the speed limit. Data and parameters used in the firstand second merge models to determine the merge achievability can beobtained from traffic information that is received from an externalsource, for example, by the input interface circuitry 151 and/or thecommunication devices 170. The traffic information can be real-timetraffic information or previously collected traffic information. In anexample, the ramp 711A is referred to as an easy ramp and the merge isreferred to as an easy merge when the merge for the vehicle 721A ontothe lane 712A via the ramp 711A is in one of the levels I-III. The ramp711A is referred to as a difficult ramp and the merge is referred to asa difficult merge when the merge for the vehicle 721A onto the lane 712Avia the ramp 711A is in one of the levels IV-V. Other suitable methodsor models can also be used to determine the merge achievability.

Table 4 shows the merge achievability for the ramps 471-481.

TABLE 4 Merge achievability Merge Ramp achievability 471 I 472 II 473 II474 I 475 IV 476 II 477 III 478 II 479 II 480 II 481 I

The merging achievability shown in Table 4 can also be displayedgraphically. FIGS. 9A-9D show exemplary graphic displays of the mergingachievability of the ramps 471-481 overlaid on the second map 402. Morespecifically, FIG. 9A highlights the ramps 471, 474, and 481 (dashedlines) that have the level I merging achievability. FIG. 9B highlightsthe ramps 472-473, 476, and 478-480 (dashed lines) that have the levelII merging achievability. FIG. 9C highlights the ramp 477 (dashed line)that has the level III merging achievability. FIG. 9D highlights theramp 475 (dashed line) that has the level IV merging achievability. Theramps 471-481 do not have the level V merging achievability. Of course,other display methods can be used to show the merge achievability, forexample, by using different symbols and/or colors to represent differentmerge achievability.

FIG. 9E shows a histogram 910 of the merging achievability of the ramps471-481. More specifically, numbers of the ramps for the levels I-Vmerging achievability are 3, 6, 1, 1, and 0, respectively.

As described above, merging achievability can depend on a merge model.FIGS. 10A-10L show various effects of merge models on the mergingachievability obtained from a large number of ramps in a region (notshown). Each of the FIGS. 10A-10L shows a histogram for the level I-Vmerge achievability.

The first merge model is used for FIGS. 10A, 10E, and 10I in a column1011. FIGS. 10A, 10E, and 10I correspond to merging speeds of vehiclesbeing 0.8, 0.9, and 1 times that of speed limits of roads merged onto.

The second merge model is used for columns 1012-1014. FIGS. 10B, 10F,and 10J in the column 1012 correspond to merging speeds of vehiclesbeing 0.8, 0.9, and 1 times that of speed limits of roads merged ontoand a TD duration of 3 seconds. FIGS. 10C, 10G, and 10K in the column1013 correspond to merging speeds of vehicles being 0.8, 0.9, and 1times that of speed limits of roads merged onto and the TD duration of 4seconds. FIGS. 10D, 10H, and 10L in the column 1014 correspond tomerging speeds of vehicles being 0.8, 0.9, and 1 times that of speedlimits of roads merged onto and the TD duration of 5 seconds.

Effects of the merge model can be seen by comparing FIGS. 10A-L. In anexample, effects of the merging speed can be seen by comparing graphswithin each column. For example, within each column, as the mergingspeed increases, a number of the level II merge achievability decreasesand a number of the level V merge achievability increases. Effects ofthe TD duration can be seen by comparing graphs within each of rows1021-1023 of the columns 1012-1014. For example, within each row, as theTD duration increases, a number of the level I merge achievabilitydecreases and a number of the level V merge achievability increases.

In addition to the merge achievability levels described above, a mergedistance can be determined. The merge distance can be determineddifferently based on, for example, different models. Referring to FIG.7A, in certain models, the merge distance refers to a distance withinwhich the vehicle 721A can merge onto the road 710A via the ramp 711A.In certain models, the merge distance refers to a distance between afirst position where the vehicle can see the road 710A and startplanning a merge maneuver and a second position where the vehicle mergesonto the road 710A.

FIG. 11 shows a histogram 1100 of merge distances of a large number oframps in a region (not shown). The histogram 1100 indicates that amajority of ramps has merge distances between 100 and 550 m. In anexample, a longer merge distance corresponds to a more difficult merge,e.g., the level IV merge achievability corresponds to a longer mergedistance than that of the level I merge achievability.

FIG. 7B shows a diverging example 700B. A road 710B has lanes 712B-713B.In an example, the road 710B is a highway. Vehicles 722B-723B run on thelanes 712B-713B, respectively. A ramp 711B is located next to the lane712B. A vehicle 721B diverges from the road 710B via the ramp 721B.

FIG. 7C shows a merging/diverging example 700C. A road 710C has lanes712C-713C. In an example, the road 710C is a highway. Vehicles 722C-723Crun on the lanes 712C-713C, respectively. A ramp 711C is located next tothe lane 712C. In an example, the vehicle 721C can stay on the ramp 721Cwithout merging onto the road 710C. Alternatively, the vehicle 721C canmerge onto the road 710C and then diverge from the road 710C via theramp 711C.

FIG. 12 shows a histogram 1200 of merge/diverge distances of a largenumber of ramps in a region. The merge/diverge distance refers to adistance within which the vehicle 721C can merge onto and then divergefrom the road 710C via the ramp 711C. Referring to FIGS. 11 and 12 , anaverage merge/diverge distance is longer than an average merge distance.

Merging/diverging achievability of ramps can depend on a merge model.FIGS. 13A-13L show various effects of merge models on themerging/diverging achievability based on a large number of ramps in aregion (not shown). Each of the FIGS. 13A-L shows a histogram for thelevel I-V merge achievability.

The first merge model is used for FIGS. 13A, 13E, and 13I in a column1311. FIGS. 13A, 13E, and 13I correspond to merging speeds of vehiclesbeing 0.8, 0.9, and 1 times that of speed limits of roads mergedonto/diverge from.

The second merge model is used for columns 1312-1314. FIGS. 13B, 13F,and 13J in the column 1312 correspond to merging speeds of vehiclesbeing 0.8, 0.9, and 1 times that of speed limits of roads mergedonto/diverge from and a TD duration of 3 seconds.

FIGS. 13C, 13G, and 13K in the column 1313 correspond to merging speedsof vehicles being 0.8, 0.9, and 1 times that of speed limits of roadsmerged onto/diverge from and the TD duration of 4 seconds.

FIGS. 13D, 13H, and 13L in the column 1314 correspond to merging speedsof vehicles being 0.8, 0.9, and 1 times that of speed limits of roadsmerged onto/diverge from and the TD duration of 5 seconds.

Effects of the merge model can be seen by comparing FIGS. 13A-L. In anexample, effects of the merging speed can be seen by comparing graphswithin each column. For example, within each column, as the mergingspeed increase, a number of the level II merge/diverge achievabilitydecreases and a number of the level I merge/diverge achievabilityincreases. Effects of the TD duration can be seen by comparing graphswithin each of rows 1321-1323 of the columns 1312-1314. For example,within each row, as the TD duration increase, numbers of the level I andII merge achievability decrease and numbers of the level IV and V mergeachievability increase.

Referring back to FIG. 2 , at S230, at least one route based on the roadcomplexity can be obtained. As described above, the routing module 133can implement the step S230 and obtain the at least one route thatsatisfies certain criteria. In an example, the criteria can include alength requirement such as “the route is longer than a first length,such as 1 km, and shorter than a second length, such as 10 km”. The atleast one route can be sent to the output interface circuitry 152 and/orthe communication devices 170. The process 200 proceeds to S299, andterminates.

The process 200 can be applied to any roads or connected roads havingany suitable length. For example, lengths of the connected roads can beabove the first threshold, such as 100 m, 500 m, 1 km, or the like. Inan example, a length of a road or a connected road can have an order ofmagnitude of 100 miles. The process 200 can be applied to any region,such as multiple countries, the United States, a portion of the UnitedState, or the like. The process 200 can also be adapted. In variousexamples, the second map 402 can also include one or more road segmentsare not connected. The first map 401 can also be divided recursivelywhere one or more of the first sub-maps 401A-D are further divided intosmaller maps.

FIG. 3 is a flowchart outlining an exemplary process 300 implementedusing, for example, the apparatus 100 or the connection module 131 asshown in FIG. 1 . The process 300 can be used to combine a plurality ofshort road segments in a first map into a connected road in a secondmap. The process 300 starts at S301 and proceeds to S310.

At S310, a first map having road segments can be obtained for a regionto be analyzed. Lengths of the road segments can be less than the firstthreshold, such as 100 m. The first map can be a HD map.

At S320, whether to divide the first map is determined, for example,based on a size of the region, a number of the road segments in thefirst map, and/or the like. In an example, when the number of the roadsegments exceeds the number threshold, the first map is divided and theprocess 300 proceeds to S340. Otherwise, the first map remainsundivided, and the process 300 proceeds to S330.

At S330, the second map is determined based on the first map bycombining the road segments in the first map into connected roads in thesecond map. For example, referring to FIGS. 4A and 4D, the road segments411-437 in the first map 401 are combined into the connected roads461-469 in the second map 402.

A suitable order can be used to connect the road segments 411-437 intothe connected roads 461-469. In an example, a connected road, such asthe connected road 461 starts from a dead end in the first map 401,e.g., the road segment 411, that is also a first end of the connectedroad 461. A number of road segments (i.e., the road segment 412)adjacent to the road segment 411 can be determined. When the number isequal to 1, the connected road 461 includes the road segment 412. Theabove process can be implemented iteratively for the road segments413-415, and thus the connected road 461 is also determined to includethe road segments 413-415. When a number of road segments (i.e., theroad segments 418-419) adjacent to the road segment 415 is determined tobe larger than 1, the road segment 415 is determined to be at a secondend of the connected road 461. Accordingly, the connected road 461includes the first end 411, the second end 415, and the road segments412-414 between the first and second ends 411 and 415.

Another connected road can start from a new first end. The new first endcan be the road segment 418 or 419 that is adjacent to the road segment415. Alternatively, the new first end can be a dead end 416 of the firstmap 401. Similar methods used to form the connected road 461 can be usedto determine the other connected road.

The order to connect the road segments 411-437 into the connected roads461-469 can be from a dead end (e.g., the road segment 411) of the firstmap 401 to a center (e.g., the road segment 415) of the first map 401.The order can also be from a center (e.g., the road segment 418) of thefirst map 401 to a dead end (e.g., the road segment 416). The order canalso be from one center (e.g., the road segment 419) to another center(e.g., the road segment 421). The order can also be from one dead end toanother dead end (not shown). One or more orders can be combined toconnect the road segments 411-437 in the first map 401. The process 300proceeds to S399, and terminates. Lengths of the connected roads can belonger than the first threshold.

In an example, when the number of the road segments is large, the stepS330 can take a long time to implement. An alternative method usingsteps S340, S350, and S360 is described below.

At S340, the first map is divided into multiple first sub-maps. Thefirst map can be divided into a suitable number of the first sub-maps,such as 2, 3, or the like. Sub-regions for the first sub-maps can havesuitable sizes and shapes. In the example shown in FIG. 4B, the firstmap 401 is divided into the 4 first sub-maps 401A-D having a same sizeand a same shape.

At S350, second sub-maps are determined based on the first sub-maps,respectively. The second sub-maps include sub-roads that are formed bycombining a plurality of road segments in the respective first sub-maps,as described with reference to FIGS. 4B-4C. The second sub-maps 402A-Dcan be determined in a parallel process from the respective firstsub-maps 401A-D, thus can be determined faster than determining thesecond map 402 directly from the first map 401. As described above, thefirst map 401 includes the dead ends 411, 416, 426, 428, 429, and 437and the connected road segments, such as the road segments 412-415. Whenthe first map 401 is divided into the 4 first sub-maps 401A-D, a subsetof the connected road segments in the first map 401 becomes dead ends inthe respective first sub-maps 401A-D. More specifically, the connectedroad segments 413 and 436, 414 and 419, 435 and 432, and 420 and 433 inthe first map 401 become the dead ends in the respective first sub-maps401A-D.

Within each first sub-map, an order to connect road segments intoconnected sub-roads can be from a dead end of the first sub-map to acenter of the first sub-map, from a dead end of the first sub-map toanother dead end of the first sub-map, from a center to a dead end ofthe first sub-map, and from a center to another center of the firstsub-map. Accordingly, referring to FIG. 4C, the sub-roads 441-442 aredetermined for the second sub-map 402A; the sub-roads 443-444 aredetermined for the second sub-map 402B; the sub-road 445 is determinedfor the second sub-map 402C; and the sub-roads 446-450 are determinedfor the second sub-map 402D. As described above, the road segment 419remains unconnected in the second sub-map 402B, and the road segments432 and 435 remain unconnected in the second sub-map 402C.

At S360, the sub-roads in the second maps are combined into connectedroads in the second map. Multiple sub-roads across multiple sub-maps canbe combined into a connected road via the respective dead ends in themultiple sub-maps. For example, the sub-road 441 in the second sub-map402A and the sub-road 444 in the second sub-map 402B are combined intothe connected road 461 via the dead ends 413 and 414 in the secondsub-map 402A-402B, respectively. In various examples, one or more of theconnected roads can also include one or more of the road segments thatare not connected to a connected sub-road in a first sub-map. The roadsegment 419 in the second sub-map 402B and the sub-road 446 in thesecond sub-map 402D are combined into the connected road 463 via thedead ends 419-420 in the second sub-map 402B and 402D, respectively. Thesub-road 442 in the second sub-map 402A and the road segment 435 in thesecond sub-map 402C are combined into the connected road 465 via thedead ends 436 and 435, respectively. The road segment 432 in the secondsub-map 402C and the sub-road 447 in the second sub-map 402D arecombined into the connected road 464 via the dead ends 432-433. Theprocess 300 proceeds to S399, and terminates.

While aspects of the present disclosure have been described inconjunction with the specific embodiments thereof that are proposed asexamples, alternatives, modifications, and variations to the examplesmay be made. Accordingly, embodiments as set forth herein are intendedto be illustrative and not limiting. There are changes that may be madewithout departing from the scope of the claims set forth below.

What is claimed is:
 1. An apparatus comprising: interface circuitryconfigured to obtain a first map of a region having road segments, thefirst map including first nodes located at edges of the first map,second nodes separating two adjacent road segments, and third nodesseparating more than two adjacent road segments; processing circuitryconfigured to: connect adjacent road segments that are separated by thesecond nodes and are not separated by the third nodes to form respectiveconnected roads, an end of each of the connected roads being one of (i)the first nodes and (ii) the third nodes, a length of one of theconnected roads being longer than a threshold, the threshold beingselected to allow for curve information to be determined accurately inthe connected road, wherein curve information could not have beendetermined accurately using the individual road segments that wereconnected to form the connected road; determine, based on the first maphaving the road segments, a second map having the connected roads;determine road complexity of one of the connected roads in the secondmap for route planning and testing, the road complexity including curveinformation and one of: ramp information, lane information, orientationinformation, hill information, tunnel information, and speed limitinformation of the one of the connected roads; and control a vehicle tomove along a particular route and to test the vehicle in operation,based on the determined road complexity; and memory to store the roadcomplexity of the one of the connected roads.
 2. The apparatus of claimI, wherein lengths of the road segments are shorter than the threshold.3. The apparatus of claim 1, wherein the processing circuitry is furtherconfigured to: determine whether the first map is to be divided; andwhen the first map is determined to be divided, divide the first mapinto multiple first sub-maps; determine, based on the first sub-maps,second sub-maps by connecting the road segments into connectedsub-roads; and combine the connected sub-roads in the second sub-maps toform the connected roads in the second map.
 4. The apparatus of claim 3,wherein the processing circuitry is configured to determine whether thefirst map is to be divided based on at least one of: a number of theroad segments and a size of the region.
 5. The apparatus of claim 1,wherein the one of the connected roads includes a ramp; and theprocessing circuitry is further configured to determine mergeachievability for the ramp based on the road complexity of the one ofthe connected roads and information of a vehicle to merge onto the oneof the connected roads.
 6. The apparatus of claim 5, wherein theprocessing circuitry is further configured to implement a merge modelthat includes a transition period when the vehicle is controlled by adriver of the vehicle and an automatic period when the vehicle iscontrolled automatically.
 7. The apparatus of claim 5, wherein the roadcomplexity includes a ramp distance and a speed limit of the one of theconnected roads, and the information of the vehicle includes a maximumspeed of the vehicle and a maximum acceleration of the vehicle.
 8. Theapparatus of claim 1, wherein the processing circuitry is furtherconfigured to obtain at least one route based on the road complexity. 9.A method, comprising: obtaining, by interface circuitry of an apparatus,a first map of a region having road segments, the first map includingfirst nodes located at edges of the first map, second nodes separatingtwo adjacent road segments, and third nodes separating more than twoadjacent road segments; connecting, by processing circuitry of theapparatus, adjacent road segments that are separated by the second nodesand are not separated by the third nodes to form respective connectedroads, an end of each of the connected roads being one of (i) the firstnodes and (ii) the third nodes, a length of one of the connected roadsbeing longer than a threshold, the threshold being selected to allow forcurve information to be determined accurately in the connected road,wherein curve information could not have been determined accuratelyusing the individual road segments that were connected to form theconnected road; determining, based on the first map having the roadsegments, a second map having the connected roads; determining roadcomplexity of one of the connected roads in the second map for routeplanning and testing, the road complexity including curve informationand one of: ramp information, lane information, orientation,information, hill information, tunnel information, and speed limitinformation of the one of the connected roads; controlling a vehicle tomove along a particular route and to test the vehicle in operation,based on the determined road complexity; and storing the road complexityof the one of the connected roads in memory of the apparatus.
 10. Themethod of claim 9, wherein lengths of the road segments are shorter thanthe threshold.
 11. The method of claim 9, wherein determining the secondmap further comprises: determining whether the first map is to bedivided; and when the first map is determined to be divided, dividingthe first map into multiple first sub-maps; determining, based on thefirst sub-maps, second sub-maps by connecting the road segments intoconnected sub-roads; and combining the connected sub-roads in the secondsub-maps to form the connected roads in the second map.
 12. The methodof claim 11, wherein determining whether the first map is to be dividedfurther comprises determining whether the first map is to be dividedbased on at least one of: a number of the road segments and a size ofthe region.
 13. The method of claim 9, wherein the one of the connectedroads includes a ramp; and determining the road complexity furthercomprises determining merge achievability for the ramp based on the roadcomplexity of the one of the connected roads and information of avehicle to merge onto the one of the connected roads.
 14. The method ofclaim 13, wherein determining the road complexity comprises implementinga merge model that includes a transition period when the vehicle iscontrolled by a driver of the vehicle and an automatic period when thevehicle is controlled automatically.
 15. The method of claim 9, furthercomprising: obtaining at least one route based on the road complexity.16. A non-transitory computer readable storage medium havinginstructions stored thereon that when executed by processing circuitrycauses the processing circuitry to perform a method, the methodcomprising: obtaining a first map of a region having road segments, thefirst map including first nodes located at edges of the first map,second nodes separating two adjacent road segments, and third nodesseparating more than two adjacent road segments; connecting adjacentroad segments that are separated by the second nodes and are notseparated by the third nodes to form respective connected roads, an endof each of the connected roads being one of (i) the first nodes and (ii)the third nodes, a length of one of the connected roads being longerthan a threshold, the threshold being selected to allow curveinformation to be determined accurately in the connected road, whereincurve information could not have been determined accurately using theindividual road segments that were connected to form the connected road;determining, based on the first map having the road segments, a secondmap having the connected roads; determining road complexity of one ofthe connected roads in the second map for route planning and testing,the road complexity including curve information and one of: rampinformation, lane information, orientation information, hillinformation, tunnel information, and speed limit information of the oneof the connected roads; controlling a vehicle to move along a particularroute and to test the vehicle in operation, based on the determined roadcomplexity; and storing the road complexity of the one of the connectedroads.